Refresh Wellness Application: developing mental wellness tools using AI

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People experiencing mental wellness challenges or mental illness often struggle to obtain or maintain a position in the workplace. This costs the Canadian economy $50B/yr and results in five hundred thousand unemployed citizens. With lack of employment, individuals also lose mental, emotional, and physiological benefits generated through work. Disconnection perpetuates further psychological sickness. In response, the Digital Integration Centre of Excellence (DICE) at Saskatchewan Polytechnic (Sask Polytech), Refresh Enterprises, Inc. (Refresh), and the Canadian Mental Health Association, Saskatchewan Division (CMHA-SK) are collaborating to finalize the development of the Refresh Wellness App (RWA), a multifaceted lifestyle program that will promote healthy mentality and facilitate relational support through peers and professionals. RWA will leverage artificial intelligence (AI), data analytics, and automatic personality recognition (APR) technology in order to automatically respond to users' mental and emotional states, offering helpful suggestions and resources. With the individual user's permission, information could be shared with health care workers to inform their services. Service providers will be able to list themselves in the app's business directory. RWA will be a first-of-its-kind service for organizations, enabling them to analyze their corporate wellbeing as a single entity by merging data obtained from anonymized tracking of individual employees. Data encryption, anonymization, and limitation techniques will safeguard users' identities and information; local and international data management regulations will inform how the RWA handles sensitive information. In short, the Refresh Wellness App intends to become the nexus of all Canadian mental health services. Health care workers will be better connected to their patients, with access to analytic tools that will enhance their own services. Organizations will be able to both assess their strength in a completely new way and to eventually capture and utilize intersectional data.